Risk factors of mortality in Klebsiella pneumoniae bloodstream infection and construction of a prediction model for prognosis of patients / 中华临床感染病杂志

ABSTRACT

Objective:To explore the risk factors of mortality in patients with Klebsiella pneumoniae bloodstream infection, and to construct a predictive model. Methods:The clinical data of 234 patients with Klebsiella pneumoniae bloodstream infection admitted in the First Hospital of Qinhuangdao from January 2020 to December 2022 were retrospectively analyzed, including 202 cases admitted during January 2020 to June 2022 (model set), and 32 cases admitted during July to December 2022 (validation set). There were 64 cases died (fatal group) and 138 cases survived (survival group) within 28 d after admission in model set. Multivariate Logistic regression was used to analyze the risk factors of death in patients with Klebsiella pneumoniae bloodstream infection and a mortality prediction model was constructed. The constructed model was applied in validation set, and the consistency between predicted mortality and real mortality was analyzed. Results:Multivariate Logistic regression analysis showed that male sex ( OR=2.598, 95% CI 1.179-5.725, P=0.018), age≥65 years ( OR=4.420, 95% CI 2.029-9.627, P<0.001), admitted to intensive care unit (ICU) ( OR=10.299, 95% CI 4.752-22.321, P<0.001), and the empirical use of quinolones antibiotics ( OR=4.288, 95% CI 1.127-16.317, P=0.033) were independent risk factors for 28-day mortality in Klebsiella pneumoniae bloodstream infection patients. The regression equation for predicting the risk of death was -3.469+ male × 0.955+ age ≥ 65 years × 1.486+ admitted to ICU × 2.332+ empirical use of quinolone antibiotics × 1.456. The area under the ROC curve (AUC) for predicting death in the model set was 0.831, with sensitivity and specificity of 71.9% and 80.4%, respectively. The AUC for predicting death in the validation set was 0.881, with sensitivity and specificity of 91.7% and 75.0%, respectively. Conclusion:The constructed mortality prediction model in the study has good application value for the prognosis of patients with Klebsiella pneumoniae bloodstream infection.